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dc.contributor.authorRodrigues, Filipe
dc.contributor.authorAgra, Agostinho
dc.contributor.authorHvattum, Lars Magnus
dc.contributor.authorRequejo, Cristina
dc.date.accessioned2024-05-21T11:22:49Z
dc.date.available2024-05-21T11:22:49Z
dc.date.created2022-04-11T10:48:56Z
dc.date.issued2022
dc.identifier.citationJournal of Heuristics. 2022, 28 (3), 329-350.en_US
dc.identifier.issn1381-1231
dc.identifier.urihttps://hdl.handle.net/11250/3130932
dc.description.abstractLocal search algorithms are frequently used to handle complex optimization problems involving binary decision variables. One way of implementing a local search procedure is by using a mixed-integer programming solver to explore a neighborhood defined through a constraint that limits the number of binary variables whose values are allowed to change in a given iteration. Recognizing that not all variables are equally promising to change when searching for better neighboring solutions, we propose a weighted iterated local branching heuristic. This new procedure differs from similar existing methods since it considers groups of binary variables and associates with each group a limit on the number of variables that can change. The groups of variables are defined using weights that indicate the expected contribution of flipping the variables when trying to identify improving solutions in the current neighborhood. When the mixed-integer programming solver fails to identify an improving solution in a given iteration, the proposed heuristic may force the search into new regions of the search space by utilizing the group of variables that are least promising to flip. The weighted iterated local branching heuristic is tested on benchmark instances of the optimum satisfiability problem, and computational results show that the weighted method is superior to an alternative method without weights.en_US
dc.language.isoengen_US
dc.relation.urihttps://doi.org/10.1007/s10732-022-09496-2
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleWeighted iterated local branching for mathematical programming problems with binary variablesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber329-350en_US
dc.source.volume28en_US
dc.source.journalJournal of Heuristicsen_US
dc.source.issue3en_US
dc.identifier.doi10.1007/s10732-022-09496-2
dc.identifier.cristin2016657
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal